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A Text Mining-Based Framework for Constructing an RDF-Compliant Biodiversity Knowledge Repository

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Book cover Information Management and Big Data (SIMBig 2015, SIMBig 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 656))

Abstract

In our aim to make the information encapsulated by biodiversity literature more accessible and searchable, we have developed a text mining-based framework for automatically transforming text into a structured knowledge repository. A text mining workflow employing information extraction techniques, i.e., named entity recognition and relation extraction, was implemented in the Argo platform and was subsequently applied on biodiversity literature to extract structured information. The resulting annotations were stored in a repository following the emerging Open Annotation standard, thus promoting interoperability with external applications. Accessible as a SPARQL endpoint, the repository facilitates knowledge discovery over a huge amount of biodiversity literature by retrieving annotations matching user-specified queries. We present some use cases to illustrate the types of queries that the knowledge repository currently accommodates.

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Notes

  1. 1.

    http://www.biodiversitylibrary.org.

  2. 2.

    http://argo.nactem.ac.uk.

  3. 3.

    http://wiki.miningbiodiversity.org/doku.php?id=guidelines.

  4. 4.

    http://www.openannotation.org/spec/core.

  5. 5.

    https://jena.apache.org/documentation/tdb.

  6. 6.

    https://jena.apache.org/documentation/fuseki2.

  7. 7.

    http://nactem.ac.uk/copious-demo/annotations/sparql.

  8. 8.

    https://www.getpostman.com.

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Acknowledgments

We would like to thank Prof. Marilou Nicolas for her valuable inputs. This work is funded by the British Council [172722806 (COPIOUS)], and is partially supported by the Engineering and Physical Sciences Research Council [EP/1038099/1 (CDT)].

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Authors and Affiliations

  1. School of Computer Science, University of Manchester, Manchester, M13 9PL, UK

    Riza Batista-Navarro, Chrysoula Zerva, Nhung T. H. Nguyen & Sophia Ananiadou

Authors
  1. Riza Batista-Navarro
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  2. Chrysoula Zerva
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  3. Nhung T. H. Nguyen
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  4. Sophia Ananiadou
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Corresponding author

Correspondence to Sophia Ananiadou .

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Editors and Affiliations

  1. College of Medicine, University of Florida, Gainesville, Florida, USA

    Juan Antonio Lossio-Ventura

  2. Faculty of Engineering, Universidad del Pacífico, Jesús María, Lima, Peru

    Hugo Alatrista-Salas

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Batista-Navarro, R., Zerva, C., Nguyen, N.T.H., Ananiadou, S. (2017). A Text Mining-Based Framework for Constructing an RDF-Compliant Biodiversity Knowledge Repository. In: Lossio-Ventura, J., Alatrista-Salas, H. (eds) Information Management and Big Data. SIMBig SIMBig 2015 2016. Communications in Computer and Information Science, vol 656. Springer, Cham. https://doi.org/10.1007/978-3-319-55209-5_3

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  • DOI: https://doi.org/10.1007/978-3-319-55209-5_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-55208-8

  • Online ISBN: 978-3-319-55209-5

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